





import os

import pytest
from attr import dataclass


__A							:			int         =			"us-east-1"  # defaults region







@dataclass
class      lowerCamelCase:
     '''simple docstring'''


     __magic_name__   =			42
     __magic_name__   =			'arn:aws:iam::558105141721:role/sagemaker_execution_role'
     __magic_name__   =			{
         'task_name': 'mnli',
         'per_device_train_batch_size': 16,
         'per_device_eval_batch_size': 16,
         'do_train': True,
         'do_eval': True,
         'do_predict': True,
         'output_dir': '/opt/ml/model',
         'overwrite_output_dir': True,
         'max_steps': 500,
         'save_steps': 5_500,
     }
     __magic_name__   =			{**hyperparameters, 'max_steps': 1_000}




     @property
     def        lowerCAmelCase__		(    self							):
         if self.framework == "pytorch":
             return [
                 {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
                 {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
                 {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
             ]
         else:
             return [
                 {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
                 {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
                 {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
             ]




     @property
     def        lowerCAmelCase__		(    self							):
         return F"{self.framework}-transfromers-test"




     @property
     def        lowerCAmelCase__		(    self							):
         return F"./tests/sagemaker/scripts/{self.framework}"




     @property
     def        lowerCAmelCase__		(    self							):
         if self.framework == "pytorch":
             return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
         else:
             return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"





@pytest.fixture(scope='class'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Dict:




    """simple docstring"""




    _A     =							SageMakerTestEnvironment(framework=request.cls.framework				)






from math import isqrt, loga


def 				lowerCAmelCase__       (			a__ )      ->list[int]:




  '''simple docstring'''

  _UpperCamelCase           =    [True] * max_number
  for i in range(2    ,     isqrt(max_number - 1 ) + 1 ):
    if is_prime[i]:
      for j in range(i**2    ,     a__    ,     a__ ):
        _UpperCamelCase           =    False

  return [i for i in range(2    ,     a__ ) if is_prime[i]]


def 				lowerCAmelCase__       (			a__ = 800_800    ,     a__ = 800_800 )      ->int:




  '''simple docstring'''

  _UpperCamelCase           =    degree * loga(a__ )
  _UpperCamelCase           =    int(a__ )
  _UpperCamelCase           =    calculate_prime_numbers(a__ )

  _UpperCamelCase           =    0
  _UpperCamelCase           =    0
  _UpperCamelCase           =    len(a__ ) - 1
  while left < right:
    while (
        prime_numbers[right] * loga(prime_numbers[left] )
        + prime_numbers[left] * loga(prime_numbers[right] )
        > upper_bound
    ):
      right -= 1
    hybrid_integers_count += right - left
    left += 1

  return hybrid_integers_count


if __name__ == "__main__":
   print(F"{solution() = }")




